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Open Access Research article

Mapping main, epistatic and sex-specific QTL for body composition in a chicken population divergently selected for low or high growth rate

Georgina A Ankra-Badu18, Daniel Shriner2, Elisabeth Le Bihan-Duval3, Sandrine Mignon-Grasteau3, Frédérique Pitel4, Catherine Beaumont3, Michel J Duclos3, Jean Simon3, Tom E Porter5, Alain Vignal4, Larry A Cogburn6, David B Allison17, Nengjun Yi17 and Samuel E Aggrey8*

Author Affiliations

1 Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, USA

2 National Institutes of Health/The National Human Genome Research Institute, Bethesda, MD 20892, USA

3 Institut Nationale de la Recherche Agronomique, UR83 Recherche Avicoles, F-37380 Nouzilly, France

4 INRA, Laboratoire de Genetique Cellulaire, 31326 Castanet-Tolosan, France

5 Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA

6 Department of Animal and Food Sciences, University of Delaware, Newark, DE 19717, USA

7 Clinical Nutrition Research Center, University of Alabama, Birmingham, AL 35294, USA

8 Department of Poultry Science/Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA

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BMC Genomics 2010, 11:107  doi:10.1186/1471-2164-11-107

Published: 11 February 2010

Abstract

Background

Delineating the genetic basis of body composition is important to agriculture and medicine. In addition, the incorporation of gene-gene interactions in the statistical model provides further insight into the genetic factors that underlie body composition traits. We used Bayesian model selection to comprehensively map main, epistatic and sex-specific QTL in an F2 reciprocal intercross between two chicken lines divergently selected for high or low growth rate.

Results

We identified 17 QTL with main effects across 13 chromosomes and several sex-specific and sex-antagonistic QTL for breast meat yield, thigh + drumstick yield and abdominal fatness. Different sets of QTL were found for both breast muscles [Pectoralis (P) major and P. minor], which suggests that they could be controlled by different regulatory mechanisms. Significant interactions of QTL by sex allowed detection of sex-specific and sex-antagonistic QTL for body composition and abdominal fat. We found several female-specific P. major QTL and sex-antagonistic P. minor and abdominal fatness QTL. Also, several QTL on different chromosomes interact with each other to affect body composition and abdominal fatness.

Conclusions

The detection of main effects, epistasis and sex-dimorphic QTL suggest complex genetic regulation of somatic growth. An understanding of such regulatory mechanisms is key to mapping specific genes that underlie QTL controlling somatic growth in an avian model.